EP-4152657-B1 - DATA ANALYSIS METHOD, ELECTRONIC DEVICE, AND STORAGE MEDIUM

Inventors

• LIU, JIANWEI
• HAN, Jing
• DONG, Xinyou

Dates

Publication Date

20260506

Application Date

20210330

Claims (7)

1. A data analysis method, comprising: (S101), obtaining network performance index data before a network is updated as a first data, and obtaining network performance index data after the network is updated as a second data; (S202), calculating a deviation rate of the second data relative to the first data; (S303), calculating a significance test probability of the network performance index according to the first data and the second data; (S304), outputting the network performance index whose deviation rate is greater than the first preset threshold and whose significance test probability is less than a second preset threshold; (S305), using each network performance index whose deviation rate is greater than the first preset threshold and whose significance test probability is less than the second preset threshold as a target network performance index; (S306), calculating an average change rate of a plurality of target network performance indexes according to the first data and the second data; (S307), calculating an index change degree of the plurality of target network performance indexes according to the deviation rate and the average change rate; and (S308), sorting the plurality of target network performance index according to the index change degree, and outputting the sorted target network performance index.
2. The data analysis method of claim 1, wherein the calculating the deviation rate of the second data relative to the first data comprises: calculating the deviation rate of the second data relative to the first data in a preset time window.
3. The data analysis method of claim 1, wherein before the outputting the sorted target network performance index, the data analysis method further comprises: obtaining a sub-index of the target network performance index, and calculating a deviation rate of sub-index data after the network update relative to sub-index data before the network update, wherein the sub-index is a related index for calculating the target network performance index; the outputting the sorted target network performance index comprises: outputting the sorted target network performance index and the sub-index whose deviation rate is greater than the first preset threshold.
4. The data analysis method of claim 1, wherein the calculating the index change degree of the target network performance index according to the deviation rate and the average change rate comprises: calculating the index change degree according to a formula DC=diff_ratio a * |CR| b , wherein DC is the index change degree, diff_ratio is a data deviation rate, CR is the average change rate, a is greater than 1, and b is greater than 0 and less than 1.
5. The data analysis method of claim 4, wherein CR is calculated according to a formula CR = 2*( data at - data bf ) / ( data at + data bf ), data at is an average value of the second data, and data bf is an average value of the first data.
6. An electronic device, comprising: at least one processor (401); and a memory (402) communicated with the at least one processor (401), wherein the memory (402) stores instructions executable by the at least one processor (401), and the instructions are executed by the at least one processor (401), to cause the at least one processor (401) to execute the data analysis method of any one of claims 1 to 5.
7. A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor (401), it causes the processor to perform the data analysis method of any one of claims 1 to 5.

Description

TECHNICAL FIELD The present application relates to the technical field of communications, and in particular to a data analysis method, an electronic device and a storage medium. BACKGROUND In order to meet the communication needs of daily life, commerce and public services, or the like, the communication network needs to ensure continuous and stable operation. However, in order to improve network performance or user experience, the communication network system needs to perform some major operations, such as frequently modify network parameters and upgrade versions. These major operations may bring instability to the communication network, and it is necessary to evaluate the network performance before and after the operation to determine whether the major operations are appropriate. If the major operations are not appropriate, a fallback is required to ensure the stable operation of the communication network. At present, in order to evaluate the network performance before and after the major operation, network operation and maintenance personnel design multiple network performance index data, and evaluate the effect of the major operation according to the changes of each network performance index data before and after the operation. However, the traditional method usually requires network operation and maintenance personnel to manually compare the changes of multiple network performance indexes before and after the operation, which requires a lot of labor costs, and the evaluation efficiency is low. EP3544330A1 discloses a network configuration change validation environment, and is related to an interface to initiate automated test actions (e.g., network monitoring commands, application monitoring commands, etc.) and to view results in an efficient manner to support a network communication infrastructure. In one example, results of a set of commands executed prior to a configuration change may serve as a baseline and one or more results of the same set of commands may be intelligently compared to the baseline to identify any potential issues that have arisen. For example, as a result of a specific network configuration change or application update. The disclosed network change validation command initiator and validation report viewer represent part of an overall network configuration change validation environment that includes automated techniques such that it may be used within a given change window. US9471455B2 discloses a method performed by a monitoring tool in a computer system, the method including: identifying a software update applied to a plurality of computer system assets, retrieving a first status of a first one of the assets from a first time period before the software update was applied to the first asset, retrieving a second status of the first asset from a second time period after the software update was applied to the first asset, determining a first effectiveness of the software update for the first asset based on comparing the first status and the second status, and displaying within a Graphical User Interface (GUI) an identification of the software update, an identification of the first asset, and a recommendation for the software update based on the first effectiveness. US20050278703A1 discloses methods for using statistical analysis to monitor performance of new network infrastructure and applications for deployment thereof. A method monitors a release of executing software applications or execution infrastructure to detect deviations in performance. A first set of time-series data is acquired from executing software applications and execution infrastructure. A first statistical description of expected behavior is derived from the first set of acquired data. A second set of time-series data is acquired from the monitored release of executing software applications and execution infrastructure. A second statistical description of behavior is derived from the second set of acquired data. The first and second statistical descriptions are compared to identify instances where the first and second statistical descriptions deviate sufficiently to indicate a statistically significant probability that an operating anomaly exists within the monitored release of executing software applications and execution infrastructure. CN107276849A discloses a kind of method for analyzing performance of cluster and device, factor of influence represents the index change of default capabilities index in the present invention, total factor of influence is to be added the factor of influence of the corresponding each server to be monitored of each default capabilities index, the index change of the performance indications of a cluster can be represented, the performance change using distributed type assemblies before and after updating can be accessed. The present invention can automatically analyze the index change of the performance indications of distributed type assemblies, no longer need manually to obtain th